Comparing Multi-Agent Path Finding Algorithms in a Real Industrial Scenario
Published in AIxIA 2022 – Advances in Artificial Intelligence, 2022
This paper compares different MAPF strategies on an industrial factory floor, assessing trade-offs in scalability, path quality, and runtime performance under real-world constraints.
Recommended citation: E. Saccon, L. Palopoli, and M. Roveri. (2023). "Comparing Multi-Agent Path Finding Algorithms in a Real Industrial Scenario." AIxIA 2022 – Advances in Artificial Intelligence, pp. 184–197. doi:10.1007/978-3-031-27181-6_13.
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